The Massachusetts Institute of Technology (MIT) announced this week a partnership with the U.S. automaker Ford to run a project aimed at improving ride-hailing services. According to the team, the LiDAR project is designed to equip electric, self-driving shuttles with cameras and sensors that help them learn and predict pedestrian movement.
The shuttles will be first tested on MIT campus in Cambridge, MA. The vehicles are also meant to provide an on-demand transport service across the campus.
Researchers at the institute’s Aeronautics and Astronautics Department Aerospace Controls Lab will also take advantage of the opportunity to test and develop new computer software that can help them with predictions and planning tasks.
Ford Ken Washington, leader of the team of engineers that created LiDAR explained that the sensors and cameras collect data on how pedestrians move to be later able to predict what the on-campus hotspots are.
- Washington added that the new technology will help his team gather precious data that could help them design better algorithms and improve the current on-campus mobility services.
- The system will also help researchers create maps and technologies that excel at pedestrian detection.
MIT researchers have already mapped foot traffic on campus via three automated vehicles that were equipped with LiDAR earlier this year. This initial data provided researchers with an insight on how students and other pedestrians move around the campus.
Next, the team plans to develop an app that would allow teachers and students hail one of the shuttles, which should make its way to the user in the shortest time due to the mobility prediction algorithms.
The tiny vehicles won’t hinder campus foot traffic as they are small enough to allow pedestrians walk freely. They will also have weather protection to prevent passengers from getting wet from bad weather.
The research team explained that the new tech detects nearby pedestrians through short pulses of laser. The tech also uses laser pulses to detect surrounding objects and determiner the vehicle’s exact location on a map.
Variations in weather and foot traffic caused by weather and the divisions of an academic year were also included in the algorithm. Vehicles now know when there will be the highest traffic and demand based on their data.
The new system will be tested on campus starting September, the university announced.
Image Source: Wikimedia